Development and simulation of DSP filters for transformer differential protection / by Oskar Reynisson.

Transformer protection is one of the most challenging applications within the power system protective relay field. Transformers with a capacity rating exceeding 10 MVA are usually protected using differential current relays. Transformers are an aging and vulnerable bottleneck in the present power grid; therefore, quick fault detection and corresponding transformer de-energization is the key element in minimizing transformer damage. Present differential current relays are based on digital signal processing (DSP). They combine DSP phasor estimation and protective-logic-based decision making. The limitations of existing DSP-based differential current relays must be identified to determine the best protection options for sensitive and quick fault detection. The development, implementation, and evaluation of a DSP differential current relay is detailed. The overall goal is to make fault detection faster without compromising secure and safe transformer operation. A detailed background on the DSP differential current relay is provided. Then different DSP phasor estimation filters are implemented and evaluated based on their ability to extract desired frequency components from the measured current signal quickly and accurately. The main focus of the phasor estimation evaluation is to identify the difference between using non-recursive and recursive filtering methods. Then the protective logic of the DSP differential current relay is implemented and required settings made in accordance with transformer application. Finally, the DSP differential current relay will be evaluated using available transformer models within the ATP simulation environment. Recursive filtering methods were found to have significant advantage over non-recursive filtering methods when evaluated individually and when applied in the DSP differential relay. Recursive filtering methods can be up to 50% faster than non-recursive methods, but can cause false trip due to overshoot if the only objective is speed. The relay sensitivity is however independent of filtering method and depends on the settings of the relay’s differential characteristics (pickup threshold and percent slope).

A COMPARATIVE STUDY AND EVALUATION OF COLLABORATIVE RECOMMENDATION SYSTEMS

Consumers currently enjoy a surplus of goods (books, videos, music, or other items) available to purchase. While this surplus often allows a consumer to find a product tailored to their preferences or needs, the volume of items available may require considerable time or effort on the part of the user to find the most relevant item. Recommendation systems have become a common part of many online business that supply users books, videos, music, or other items to consumers. These systems attempt to provide assistance to consumers in finding the items that fit their preferences. This report presents an overview of recommendation systems. We will also briefly explore the history of recommendation systems and the large boost that was given to research in this field due to the Netflix Challenge. The classical methods for collaborative recommendation systems are reviewed and implemented, and an examination is performed contrasting the complexity and performance among the various models. Finally, current challenges and approaches are discussed.